code: def np_to_dataloader(data, batch_size, num_processes):
      if batch_size % num_processes != 0:
          warnings.warn(
              "'batch_size' cannot be divided with no remainder by "
              "'self.num_processes'. We got 'batch_size' = {} and "
              "'self.num_processes' = {}".format(
                  batch_size, num_processes
              )
          )
      return DataLoader(
          TensorDataset(
              torch.from_numpy(data[0]), torch.from_numpy(data[1])
          ),
          batch_size=max(1, batch_size // num_processes),
          shuffle=True,
      )
  
imports: import torch
  import torch.nn
  import warnings
  import random
  import numpy
  from torch.utils.data import TensorDataset, DataLoader
  import numpy
  import multiprocessing
  import warnings
  import math
label_desc: Use image node_id 9 for calling a global function with example usage: np_to_dataloader(data, batch_size, num_processes) and returns: DataLoader